03765nam a22004575i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001800153072001600171072002300187082001400210100004100224245011300265264003800378300003400416336002600450337002600476338003600502347002400538490006500562505079600627520141401423650001702837650003102854650002802885650002502913650002402938650001702962650001802979650006202997650004503059710003403104773002003138776003603158830006503194856004803259978-0-387-78723-7DE-He21320180115171424.0cr nn 008mamaa100301s2008 xxu| s |||| 0|eng d a97803877872377 a10.1007/978-0-387-78723-72doi 4aQA402.5-402.6 7aPBU2bicssc 7aMAT0030002bisacsh04a519.62231 aBartholomew-Biggs, Michael.eauthor.10aNonlinear Optimization with Engineering Applicationsh[electronic resource] /cby Michael Bartholomew-Biggs. 1aBoston, MA :bSpringer US,c2008. aXVI, 280 p.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aSpringer Optimization and Its Applications,x1931-6828 ;v190 aIntroducing Optimization -- One-variable Optimization -- Applications in n Variables -- n-Variable Unconstrained Optimization -- Direct Search Methods -- Computing Derivatives -- The Steepest Descent Method -- Weak Line Searches and Convergence -- Newton and Newton-like Methods -- Quasi-Newton Methods -- Conjugate Gradient Methods -- ASummary of Unconstrained Methods -- Optimization with Restrictions -- Larger-Scale Problems -- Global Unconstrained Optimization -- Equality Constrained Optimization -- Linear Equality Constraints -- Penalty Function Methods -- Sequential Quadratic Programming -- Inequality Constrained Optimization -- Extending Equality Constraint Methods -- Barrier Function Methods -- Interior Point Methods -- A Summary of Constrained Methods -- The OPTIMA Software. aThis textbook examines a broad range of problems in science and engineering, describing key numerical methods applied to real life. The case studies presented are in such areas as data fitting, vehicle route planning and optimal control, scheduling and resource allocation, sensitivity calculations and worst-case analysis. Among the main topics covered: * one-variable optimization — optimality conditions, direct search and gradient * unconstrained optimization in n variables — solution methods including Nelder and Mead simplex, steepest descent, Newton, Gauss–Newton, and quasi-Newton techniques, trust regions and conjugate gradients * constrained optimization in n variables — solution methods including reduced-gradients, penalty and barrier methods, sequential quadratic programming, and interior point techniques * an introduction to global optimization * an introduction to automatic differentiation Chapters are self-contained with exercises provided at the end of most sections. Nonlinear Optimization with Engineering Applications is ideal for self-study and classroom use in engineering courses at the senior undergraduate or graduate level. The book will also appeal to postdocs and advanced researchers interested in the development and use of optimization algorithms. Also by the author: Nonlinear Optimization with Financial Applications, ISBN: 978-1-4020-8110-1, (c)2005, Springer. 0aMathematics. 0aMathematical optimization. 0aCalculus of variations. 0aOperations research. 0aManagement science.14aMathematics.24aOptimization.24aCalculus of Variations and Optimal Control; Optimization.24aOperations Research, Management Science.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387787220 0aSpringer Optimization and Its Applications,x1931-6828 ;v1940uhttp://dx.doi.org/10.1007/978-0-387-78723-7